AI regulation is emerging as a potential political opportunity for Democrats ahead of the November 2026 US midterm elections. As public concerns grow about artificial intelligence, employment, electricity costs, privacy, and the power of major technology companies, Democratic strategists believe stronger oversight could help their candidates connect with voters. The argument is not simply about […]
Amazon says it no longer signs nondisclosure agreements with the government agencies it works with on data centers, and has pledged more than $1 billion over five years through Built Together. We set out the timeline from Microsoft’s March pledge to Jamie Raskin’s letters, the four gaps in Amazon’s wording (contractors, shell companies, old agreements, private parties), how its water, power and pollution claims hold up, and why AI agents asking for your credit card face the same trust problem.
A Brookings paper by Columbia’s Stijn Van Nieuwerburgh estimates the AI buildout will cost $10.3 trillion from 2025 to 2032, more relative to GDP than the railroads or highways, and warns that leases, SPVs and private credit are hiding the risk. We explain the numbers, Meta’s Hyperion template, the $3.7 trillion revenue question and what businesses should do.
Oracle has sent a force majeure notice on Project Jupiter, citing potential delays in securing power. We follow the power: the unissued air permit for 2.45GW of fuel cells, the twice-rejected Green Chile pipeline, PJM’s 6.8GW capacity shortfall, gas turbines sold out to 2031, why a power delay is a hard case for force majeure, and what businesses planning AI capacity should do.
Oracle has sent a force majeure notice on Project Jupiter, the New Mexico data center campus Blue Owl’s Stack Infrastructure is building for OpenAI capacity, and the move has rattled AI financing. We explain the power delay behind it, who carries which risk across $3 billion of equity and $18 billion of loans, what Oracle’s filings show about its $664 billion backlog and $288 billion of unstarted leases, and what businesses buying AI capacity should check.
Nscale has agreed to sell Anthropic roughly $45 billion of AI computing capacity over six years, according to Bloomberg and CNBC reporting on 26 August 2026. The capacity amounts to about 460 megawatts at a West Virginia campus, fitted out with Nvidia Vera Rubin systems arriving from late 2027. This breakdown covers the reported terms, what 460 megawatts actually means, who Nscale is and how a $45 billion contract reshapes its September listing plans, the Monarch Compute Campus and its off-grid gas microgrid, the Vera Rubin generation-on-generation numbers, where the deal sits alongside Anthropic’s Google, Broadcom, Amazon, Microsoft and SpaceX commitments, the price per megawatt-year, the risks nobody is pricing, and what any of it means for organisations that buy AI rather than build it.
Chris Malone, OpenAI’s head of data centers, left the company in the week of 17 August 2026, the Wall Street Journal reported and CNBC confirmed, bringing the year’s tally of senior exits to thirteen by Business Insider’s count. This breakdown separates the confirmed facts from the inference: what OpenAI actually said about the infrastructure reorganisation, how Malone’s reporting line moved from president Greg Brockman to vice president Sachin Katti before he left, the four-way split of the data centre remit across Sachin Katti, Uday Ruddarraju, Brent Mayo and Spas Lazarov, the nine named 2026 departures with dates and stated reasons, and the second-quarter numbers that made this run of exits land harder than last year’s would have. It closes with a practical vendor-stability review any buyer can run in an afternoon.
Performance per Watt has rapidly become one of the most important benchmarks for evaluating modern artificial intelligence infrastructure. As AI models continue to grow in size and complexity, organizations are no longer focused solely on raw computing power. Instead, they are increasingly measuring how efficiently hardware converts electrical energy into useful computational work. Whether deploying […]
Akamai LLM deal analysis: what a $1.8B cloud infrastructure commitment and Cloudflare’s AI-first restructuring mean for AI inference strategy.
A source-backed guide to PCIe enterprise AI GPU planning, covering workload fit, memory, PCIe bandwidth, cooling, software support, utilization, and buying tradeoffs.
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